• Journal of Communications and Networks
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• v.17 no.5
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• pp.491-498
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• 2015

Recognition of radar emitter signals is one of core elements in radar reconnaissance systems. A novel method based on singular value decomposition (SVD) and the main ridge slice of ambiguity function (AF) is presented for attaining a higher correct recognition rate of radar emitter signals in case of low signal-to-noise ratio. This method calculates the AF of the sorted signal and ascertains the main ridge slice envelope. To improve the recognition performance, SVD is employed to eliminate the influence of noise on the main ridge slice envelope. The rotation angle and symmetric Holder coefficients of the main ridge slice envelope are extracted as the elements of the feature vector. And kernel fuzzy c-means clustering is adopted to analyze the feature vector and classify different types of radar signals. Simulation results indicate that the feature vector extracted by the proposed method has satisfactory aggregation within class, separability between classes, and stability. Compared to existing methods, the proposed feature recognition method can achieve a higher correct recognition rate.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.183-190
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• 1995

The use of ultrasound pulsed Doppler systems has become increasingly popular due to the advantages of easy measurements of blood velocity, volume blood blow, and irregularities of the circulatory system. However, the 2-D Doppler systems have several problems, such as range ambiguity, low signal to noise ratio, and slow frame rate. The mean frequency aliasing problem originating from the pulse repetition frequency is one of major limitations in pulsed Doppler systems. A conventional approach to resolve this problem is tracking the mean frequency close to and beyond the Nyquist frequency along the temporal axis. In this paper, a new concept of tracking the mean frequency along the spatial axis is proposed. The proposed technique is fault tolerant by nature and more suitable for multi gate and 2-D Doppler system than conventional methods.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.279-288
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• 1995

Ultrasonic Doppler systems for the purpose of estimating blood flow velocity, blood flow volume, and flow imaging are commonly used due to advantages of non-invasive and real time observation. Specially, the technical developments of color flow mapping (2-D Doppler) systems have made a relatively rapid progress. However, the 2-D Doppler systems have several problems, such as the range ambiguity, low signal to noise ratio, and slow frame rate. The slow frame rate problem is resolved by using the spatial average which is a method to acquire more data samples for mean frequency estimation. In this paper, spatial average method using the 2nd order sampling instead of quadrature sampling is proposed. The experimental results show that the proposed methods have good performance and easy application to the color flow mapping system.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.188-195
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• 2018

A new directional linear array structure and its signal processing method are presented to resolve the left/right ambiguity inherent in a linear array. The array structure combines an ordinary acoustic sensor array with a DIFAR (Directional Frequency Analysis and Recording) sensor array, keeping a linear array configuration and gaining a instantaneous left/right discrimination. It presents better PSRR (Port-Starboard Rejection Ratio) in low frequency band and low SNR (Signal to Noise Ratio) situation as compared with a conventional twin linear array, and good compromise to easily upgrade an existing linear array system to a new one with a left/right discrimination capability.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.170-177
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• 2014

This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.151-163
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• 2001

A two color PIV technique has been developed for visualization of complex and high speed flow in a ramjet combustor. Two color PIV has the advantages that velocity distributions in high speed flowfields can be measured simply by varying the time interval between two different laser beams and a directional ambiguity problem can be solved by color separation, and then a signal-to-noise ratio can be increased through nearly perfect cross-correlation. As a basic research of the ramjet engine, a 2-D shaped combustor with two symmetric air intakes has been manufactured and an experimental study has been conducted using a two color PIV technique. The flow characteristics such as recirculation zones, intake air mixing and turbulent kinetic energy have been investigated varying inlet angles and dome heights. It was found that the primary recirculation zone is affected mainly by the dome height, whereas the secondary recirculation zone is influenced by the air inlet angle.

• The Journal of the Acoustical Society of Korea
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• v.14 no.6
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• pp.27-31
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• 1995

In this paper, the determination method of available bandwidth for automation of the split-spectrum processing(SSP) has been studied. The SSP is used for the visibility enhancement of the ultrasonic signal with grain noise. Even though the SSP has proved useful in signal-to-noise ratio enhancement, its application and automation have been limited due to ambiguity in the determination of available bandwidth. Until recently, it is the usual practice to optimize the available bandwidth by trial and error. The spectral histogram is the statistical distribution of the spectral windows that is selected by the minimization algorithm with the whole band of the spectrum of the received ultrasonic signal. Since the available bandwidth can be determined adaptively using spectral histogram, this method can be used for automation of the SSP. In order to evaluate the determination technique of the available bandwidth using spectral histogram, this method is applied to experimental ultrasonic data. The experimental results show that the spectral histogram is an efficient method for determination of the available bandwidth and automation of the SSP.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.1
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• pp.59-64
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• 2002

Passive sonar system forms the various beams in any desired directions to obtain the improvement in Signal-to-Noise(S/N) ratio, bearing detection and localization of targets, and the attenuation of interferences from other directions. Detection of modern underwater targets is becoming increasingly difficult as noise reduction technology leads to considerably low-level acoustic emissions. Therefore, the improvement of beamforming is very important to detect modern underwater targets at the long range in the complex environmental sea. Also, to react to the fast attack mobiles such as torpedoes, port and starboard discrimination is required to be performed very quickly. In this paper, we proposed the implementation of omnidirectional target bearing detector without port and starboard ambiguity to detect effectively the low-level underwater targets. The port and starboard discrimination is performed by cardioid processing and the improvement of beamforming utilizes the cross correlation matrix of individual hydrophone pairs of linear array sensors. The sea test result shows that the system implemented is good for the detection of the low-level underwater targets.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.94-102
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• 2021

This study addresses a method for 3D reconstruction using acoustic data with heterogeneous sonar devices: Forward-Looking Multibeam Sonar (FLMS) and Profiling Sonar (PS). The challenges in sonar image processing are perceptual ambiguity, the loss of elevation information, and low signal to noise ratio, which are caused by the ranging and intensity-based image generation mechanism of sonars. The conventional approaches utilize additional constraints such as Lambertian reflection and redundant data at various positions, but they are vulnerable to environmental conditions. Our approach is to use two sonars that have a complementary data type. Typically, the sonars provide reliable information in the horizontal but, the loss of elevation information degrades the quality of data in the vertical. To overcome the characteristic of sonar devices, we adopt the crossed installation in such a way that the PS is laid down on its side and mounted on the top of FLMS. From the installation, FLMS scans horizontal information and PS obtains a vertical profile of the front area of AUV. For the fusion of the two sonar data, we propose the probabilistic approach. A likelihood map using geometric constraints between two sonar devices is built and a monte-carlo experiment using a derived model is conducted to extract 3D points. To verify the proposed method, we conducted a simulation and field test. As a result, a consistent seabed map was obtained. This method can be utilized for 3D seabed mapping with an AUV.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4873-4888
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• 2018

A joint blind parameter estimation algorithm based on minimum channel stability function aimed at the non-cooperative high-order modulated paired carrier multiple access (PCMA) signals is proposed. The method, which uses hierarchical search to estimate time delay, amplitude and frequency offset and the estimation of phase offset, including finite ambiguity, is presented simultaneously based on the derivation of the channel stability function. In this work, the structure of hierarchical iterative processing is used to enhance the performance of the algorithm, and the improved algorithm is used to reduce complexity. Compared with existing data-aided algorithms, this algorithm does not require a priori information. Therefore, it has significant advantage in solving the problem of blind parameter estimation of non-cooperative high-order modulated PCMA signals. Simulation results show the performance of the proposed algorithm is similar to the modified Cramer-Rao bound (MCRB) when the signal-to-noise ratio is larger than 16 dB. The simulation results also verify the practicality of the proposed algorithm.